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trendEcon Austria

This dashboard is based on the work of trendEcon

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Perceived Economic Situation

Info

Description

The indicator for Perceived Economic Situation includes search terms that reflect people’s worries about the economy. For instance, people then google “economic crisis” (Wirtschaftskrise).

Keywords
  • Wirtschaftskrise
  • Kurzarbeit
  • arbeitslos
  • Insolvenz

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Clothing and Shoes

Info

Description

The category Clothing and Shoes includes clothing and shoe stores as well as a general search terms related to buying clothes and shoes. trendEcon found that people directly google for the brands they like. Note: the searchword “zalando” was not included because Zalando was not available in Austria before 2012.

Keywords
  • mango
  • zara
  • H&M
  • blue tomato
  • schuhe kaufen
  • deichmann

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Home Office

Info

Description

The category Home Office combine Google inquiries related to the new normal of working from home. The working-from-home-index contains the search terms:

Keywords
  • headset
  • monitor
  • maus
  • hdmi

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Gardening and Home Improvement

Info

Description

The category Gardening and Home Improvement includes stores selling materials for home improvement such as building materials, garden accessories and electrical supplies.

Keywords
  • Heim+Hobby
  • Bau+Hobby
  • Bauhaus
  • hornbach
  • obi

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Food Delivery

Info

Description

The category Food Delivery includes search terms related to take away and ordering pizza.

Keywords
  • take away
  • takeaway
  • pizza bestellen

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Cultural

Info

Description

The category Cultural Events includes search terms related to concerts, theatres, cinema and ticket providers for such events.

Keywords
  • kino
  • theater
  • cinema
  • cineplexx
  • oper
  • konzert
  • oeticket

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Travel Abroad

Info

Description

The category Travel Abroad includes search terms used to book flights and holidays.

Keywords
  • städtetrip
  • flug buchen
  • günstige flüge

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Mobility

Info

Description

The category Mobility includes search terms related to ground transportation: For instance, checking the railway schedule or calling a taxi.

Keywords
  • Fahrplan
  • taxi
  • sixt
  • google maps

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Watches and Jewelry

Info

Description

The category Watches and Jewellery includes stores and brands selling luxurious watches and jewellery goods and related, more general search terms for luxury consumer goods.

Keywords
  • juwelier
  • swarovski
  • uhr
  • uhren
  • christ
  • feichtinger

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PES

Perceived Economic Situation (monthly)

How well does the indicator coincide with the consumer confidence index and with GDP (quarterly data).

VAR

\[\mathbf{x_t^{AT}} = [ PES_t^{AT}, u_t^{AT}, P_t^{AT}] \]

Vector Autoregressive Model with 6 lags

Results

VAR(6)

dependent variables: pes, une, cpi

pes une cpi
(1) (2) (3)
pest-1 0.429*** -0.158*** 0.006
(0.082) (0.059) (0.047)

Δ unet-1

0.013 -0.129 -0.035
(0.112) (0.080) (0.064)
cpit-1 -0.068 0.075 0.062
(0.126) (0.091) (0.073)
pest-2 0.028 -0.158** -0.014
(0.090) (0.065) (0.052)

Δ unet-2

-0.143 0.110 0.097
(0.112) (0.080) (0.064)
cpit-2 0.083 0.043 -0.147**
(0.127) (0.091) (0.073)
pest-3 0.074 -0.040 0.001
(0.092) (0.066) (0.053)

Δ unet-3

0.005 -0.080 -0.015
(0.111) (0.079) (0.063)
cpit-3 0.041 0.047 0.064
(0.125) (0.090) (0.072)
pest-4 -0.006 0.242*** -0.003
(0.091) (0.065) (0.052)

Δ unet-4

0.073 -0.157** -0.009
(0.111) (0.079) (0.064)
cpit-4 0.036 0.054 -0.221***
(0.125) (0.089) (0.072)
pest-5 0.017 0.064 0.024
(0.093) (0.066) (0.053)

Δ unet-5

-0.099 -0.241*** -0.067
(0.112) (0.080) (0.064)
cpit-5 -0.052 0.074 0.022
(0.129) (0.093) (0.074)
pest-6 0.072 -0.108* -0.050
(0.088) (0.063) (0.050)

Δ unet-6

0.014 0.026 0.028
(0.113) (0.081) (0.065)
cpit-6 -0.065 0.068 0.483***
(0.131) (0.093) (0.075)
constant -0.003 -0.054 0.129***
(0.077) (0.055) (0.044)
Observations 169 169 169
R2 0.274 0.267 0.389
Adjusted R2 0.187 0.179 0.316
Residual Std. Error (df = 150) 0.568 0.407 0.326
F Statistic (df = 18; 150) 3.142*** 3.035*** 5.308***
Note: p<0.1; p<0.05; p<0.01

Summary

Data

pes - Perceived Economic Situation (Nowcasting proxy for GDP)
Dune - Unemployment rate I(2)
cpi - Inflation rate year-on-year

all variables are on a monthly frequency

Model diagnostics - residuals

(p.value threshold = 0.05)

multivariate test for serially correlated errors (Portmanteau- and Breusch-Godfrey): H0 of no serial correlation: accepted p = 0.13

multivariate Jarque-Bera tests:

H0 of Normality: rejected p = 0

H0 of Skewness = 0: rejected p = 0

H0 of Kurtosis (excess curtosis = 0): rejected p = 0

multivariate ARCH-LM test:

H0 of homoskedasticity: rejected p = 0.04

Forecasting

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Out-of sample VAR(6) Forecasting (3M ahead)

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In-sample Forecast (3M ahead)

Accuracy

Evaluation of in-sample forecast accuracy

pes Forecast accuracy:

ME RMSE MAE MPE MAPE MASE ACF1 Theil’s U
Training set 0.000 0.304 0.234 NaN Inf 1.095 0.026 NA
Test set -0.027 0.360 0.308 378.572 454.279 1.445 -0.393 3.031

Dune Forecast accuracy:

ME RMSE MAE MPE MAPE MASE ACF1 Theil’s U
Training set 0.00 0.304 0.234 NaN Inf 1.095 0.026 NA
Test set -0.55 0.951 0.855 71.979 71.979 4.006 -0.009 0.341

cpi Forecast accuracy :

ME RMSE MAE MPE MAPE MASE ACF1 Theil’s U
Training set 0.00 0.304 0.234 NaN Inf 1.095 0.026 NA
Test set 0.37 0.505 0.417 95.16 111.111 1.956 -0.448 4.298

Forecast (1M ahead)

Accuracy

Evaluation of in-sample forecast accuracy

pes Forecast accuracy:

ME RMSE MAE MPE MAPE MASE ACF1
Training set 0.000 0.308 0.236 NaN Inf 1.087 0.007
Test set -0.396 0.396 0.396 295.337 295.337 1.828 NA

Dune Forecast accuracy:

ME RMSE MAE MPE MAPE MASE ACF1
Training set 0.000 0.308 0.236 NaN Inf 1.087 0.007
Test set 0.564 0.564 0.564 68.274 68.274 2.601 NA

cpi Forecast accuracy :

ME RMSE MAE MPE MAPE MASE ACF1
Training set 0.000 0.308 0.236 NaN Inf 1.087 0.007
Test set 0.035 0.035 0.035 11.81 11.81 0.162 NA

Forecast (6M ahead)

Accuracy

Evaluation of in-sample forecast accuracy

pes Forecast accuracy:

ME RMSE MAE MPE MAPE MASE ACF1 Theil’s U
Training set 0.000 0.292 0.228 NaN Inf 1.102 0.027 NA
Test set -0.322 0.558 0.473 541.772 541.772 2.290 -0.446 4.177

Dune Forecast accuracy:

ME RMSE MAE MPE MAPE MASE ACF1 Theil’s U
Training set 0.000 0.292 0.228 NaN Inf 1.102 0.027 NA
Test set -0.807 1.018 0.899 115.311 115.311 4.348 0.081 1.482

cpi Forecast accuracy :

ME RMSE MAE MPE MAPE MASE ACF1 Theil’s U
Training set 0.000 0.292 0.228 NaN Inf 1.102 0.027 NA
Test set 0.206 0.620 0.472 126.729 163.606 2.282 -0.586 0.714